Senior Machine Learning Engineer
Core
Designing and implementing intelligent search systems, scalable serving infrastructure for ML/GenAI models, and platform capabilities to optimize user experience and relevance in real-time betting environments.
Role type
Senior Machine Learning Engineer (Search & Infrastructure)
Builds
Intelligent search systems, scalable ML/GenAI serving infrastructure, and platform features for model deployment lifecycle.
Domain
Sports betting and mobile gaming
Deliverable
production ML models | product features | infrastructure
Required skills
Python, Java, vector search, semantic search, embedding-based retrieval, typeahead/autocomplete systems, ML model deployment, scalable software architecture, distributed computing, technical leadership, data structures, cloud environments (AWS/GCP/Azure), data pipelines, vector databases.
Preferred skills
Databricks, Unity Catalog, LangChain, Hugging Face Transformers, Seldon, Arize, Flink, Spark, Kafka, Terraform, Airflow.
Technologies
PyTorch, TensorFlow, LightGBM, Keras, MLFlow, Amazon SageMaker, Amazon Bedrock, Databricks Mosaic AI, Tableau, Knime, Looker, Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis, Terraform, Airflow, AWS, GCP, Azure, Databricks, Unity Catalog, LangChain, Hugging Face Transformers, Seldon, Arize.
Responsibilities
Designing and implementing intelligent search systems incorporating typeahead, vector search, and ML personalization signals; Contributing to the design and development of scalable serving systems for ML and GenAI/LLM models; Developing platform features and capabilities for streamlining ML Model and GenAI/LLM Application development and deployment lifecycle; Designing and building data pipelines for production level ML and GenAI/LLM infrastructure; Conducting regular design process reviews and ensuring development standards within the team; Motivating junior engineers on best practices and latest industry design patterns.
Seniority
Senior, hands-on IC with technical leadership
